Settle

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Co-Founder & CTO at Settle

Build the AI-native enterprise data migration platform alongside the founder.

Apply now

From the founder

A note from Kaan

I spent years at Deloitte watching billion-dollar companies hire armies of consultants to do work that should take software hours. Enterprise data migration is one of the last great manual workflows — schema mismatches, transformation logic, validation done by hand on every customer onboarding, M&A integration, and legacy system replacement.

We're building the AI-native version: AI proposes, deterministic engines validate, humans approve. Paying enterprise customer in production today, active pipeline of mid-market software companies, in the Antler residency.

I'm hiring the person who'll own the technical side alongside me — co-founder economics, CTO scope, full ownership of agent architecture and engineering culture from day one. Cash is below market, equity is generous, and we're transparent about what that trade means.

If you've shipped LLM systems in production, care about correctness more than novelty, and want to build the system that makes enterprise data migration finally work — I want to talk.

— Kaan, Founder & CEO

The role

You'll own the full technical side of the company. Specifically:

  • Phase 3 agent architecture — design and ship the agent loop, decomposition strategy, eval harness, and validation pipeline. The next 3–6 months.
  • Engineering strategy — own technical direction, infrastructure decisions, and architectural choices as we scale.
  • Enterprise security and compliance — be the technical face in customer security reviews. Drive SOC 2 prep post-seed.
  • Hiring and team building — recruit and lead the engineering team as we grow from two to ten.
  • Customer and product — partner with the founder on product strategy, talk directly to customers, and shape the roadmap.

This role is not for someone who wants to write code in isolation. It's for someone who wants to build a company.

Who you are

Must-have

  • 5–9 years of engineering experience, with 3+ years shipping production systems used by real customers
  • Production LLM or agent system experience — has built and deployed applications using LLM APIs in production. Knows prompt engineering, structured outputs, retries, evaluation. Non-negotiable.
  • Strong backend and data fundamentals — Postgres at depth, schema design, SQL, async/queue patterns, idempotency
  • TypeScript proficient. Next.js or Node ideal.
  • Has shipped to paying customers, not just side projects

Strong preference

  • Background in data engineering, integration, migration, or ETL — alumni from Snowflake, Databricks, Airbyte, dbt Labs, Fivetran, Mulesoft, Workato, Informatica, or Talend will understand the problem viscerally
  • Enterprise SaaS instincts — already knows what SSO, RBAC, audit logs, and SOC 2 mean and why they matter
  • Has built eval frameworks (Braintrust, Langfuse, or homegrown) — Phase 3 success depends on this
  • Production cloud experience — has shipped and operated cloud-native applications in AWS, GCP, Azure, or modern PaaS (Vercel, Supabase, Render, Fly.io)

Cultural fit

  • Investigation-first — you read code before changing it
  • Comfortable presenting in enterprise security reviews
  • High agency, can decide and ship without direction
  • Direct communicator — corporate-comms styles won't fit

What we offer

  • Title: Co-Founder & CTO
  • Equity: 15–25% common stock. 4-year vest, 1-year cliff. Range based on background and timing of join.
  • Cash: $110K–$150K base. Salary ramps to $200K–$300K on seed close — written into the offer.
  • Optional structure: part of equity can be milestone-based (Series A close, eval targets) for upside alignment
  • Location: NYC. In-person.
  • Stage: Pre-seed closing. In the Antler residency. One paying enterprise customer live, multiple in pipeline.

Apply

Submit your application via the form linked below. We review every submission within 3 business days. Strong candidates get a 30-minute intro call within a week.

Apply now

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How we work

  • Investigation-first engineering — we read code before we change it
  • Two-stop pattern: investigation report → implementation
  • AI-augmented development — Cursor and Claude Code in the workflow
  • Direct communication, no filler
  • Ship frequently, validate with customers
  • Correctness over novelty
  • Enterprise-first — every architectural decision considers SOC 2, audit, RBAC